المؤلفون: René Bodjrènou, Luc Ollivier Sintondji, Françoise Comandan

المصدر: Journal of Hydrology: Regional Studies, Vol 48, Iss , Pp 101448- (2023)

مصطلحات موضوعية: ParFlow-CLM, Evaporation, Streamflow, WTD, ERA5, MERRA2, Physical geography, GB3-5030, Geology, QE1-996.5

وصف الملف: electronic resource

العلاقة: http://www.sciencedirect.com/science/article/pii/S2214581823001350Test; https://doaj.org/toc/2214-5818Test

الوصول الحر: https://doaj.org/article/f06dd7118ba34e138932f4e8e4a572a8Test

المؤلفون: Alexandre Belleflamme, Klaus Goergen, Niklas Wagner, Stefan Kollet, Sebastian Bathiany, Juliane El Zohbi, Diana Rechid, Jan Vanderborght, Harry Vereecken

المصدر: Frontiers in Water, Vol 5 (2023)

مصطلحات موضوعية: monitoring and forecasting, stakeholder relevant scales, ParFlow/CLM hydrological model, high-resolution hydrological modeling, subsurface water resources, terrestrial water budget, Environmental technology. Sanitary engineering, TD1-1066

وصف الملف: electronic resource

العلاقة: https://www.frontiersin.org/articles/10.3389/frwa.2023.1183642/fullTest; https://doaj.org/toc/2624-9375Test

الوصول الحر: https://doaj.org/article/cfea629ee8274c6da2d85258cb3ba181Test

المؤلفون: Naz, Bibi S.

المصدر: Geoscientific Model Development

مصطلحات موضوعية: ParFlow-CLM, 3 km EU-CORDEX, hydrologic modeling

العلاقة: info:eu-repo/grantAgreement/EC/H2020/824158/; https://zenodo.org/record/7716900Test; https://doi.org/10.5281/zenodo.7716900Test; oai:zenodo.org:7716900

الإتاحة: https://doi.org/10.5281/zenodo.7716900Test
https://doi.org/10.5194/gmd-2022-173Test
https://doi.org/10.5281/zenodo.7716899Test
https://zenodo.org/record/7716900Test

المؤلفون: Waldowski, Bastian, Sánchez‐León, Emilio, Cirpka, Olaf A., Brandhorst, Natascha, Hendricks Franssen, Harrie‐Jan, Neuweiler, Insa

المصدر: Water Resources Research 59 (2023), Nr. 3 ; Water Resources Research

مصطلحات موضوعية: fully integrated hydrological models, groundwater recharge, parflow-CLM, river-aquifer interactions, surface-subsurface flow, water table fluctuations, ddc:550

العلاقة: ESSN:1944-7973; http://dx.doi.org/10.15488/14838Test; https://www.repo.uni-hannover.de/handle/123456789/14957Test

الإتاحة: https://doi.org/10.15488/14838Test
https://doi.org/10.1029/2022wr032430Test
https://www.repo.uni-hannover.de/handle/123456789/14957Test

المؤلفون: Elena Leonarduzzi, Hoang Tran, Vineet Bansal, Robert B. Hull, Luis De la Fuente, Lindsay A. Bearup, Peter Melchior, Laura E. Condon, Reed M. Maxwell

المصدر: Frontiers in Water, Vol 4 (2022)

مصطلحات موضوعية: machine learning, physics-based hydrological model, ParFlow-CLM, 2D soil moisture field, convolutional neural networks, meteorological forcing scenarios, Environmental technology. Sanitary engineering, TD1-1066

وصف الملف: electronic resource

العلاقة: https://www.frontiersin.org/articles/10.3389/frwa.2022.927113/fullTest; https://doaj.org/toc/2624-9375Test

الوصول الحر: https://doaj.org/article/58fe46d8a8af416bbf109bb80cf2df76Test

المؤلفون: Leonarduzzi, E., Tran, H., Bansal, V., Hull, R.B., De la Fuente, L., Bearup, L.A., Melchior, P., Condon, L.E., Maxwell, R.M.

المساهمون: Hydrology and Atmospheric Sciences, University of Arizona

المصدر: Frontiers in Water

مصطلحات موضوعية: 2D soil moisture field, convolutional neural networks, machine learning, meteorological forcing scenarios, ParFlow-CLM, physics-based hydrological model

العلاقة: Leonarduzzi, E., Tran, H., Bansal, V., Hull, R. B., De la Fuente, L., Bearup, L. A., Melchior, P., Condon, L. E., & Maxwell, R. M. (2022). Training machine learning with physics-based simulations to predict 2D soil moisture fields in a changing climate. Frontiers in Water, 4.; http://hdl.handle.net/10150/667251Test; Frontiers in Water

الإتاحة: https://doi.org/10.3389/frwa.2022.927113Test
http://hdl.handle.net/10150/667251Test

المؤلفون: Li, Jinyang

مصطلحات موضوعية: Environmental engineering, Deep learning, Little Washita Watershed, ParFlow-CLM, Streamflow simulation, U-net

وصف الملف: application/pdf

الوصول الحر: https://escholarship.org/uc/item/2vv5n2fbTest

المؤلفون: Elena Leonarduzzi, Hoang Tran, Vineet Bansal, Robert B. Hull, Luis De la Fuente, Lindsay A. Bearup, Peter Melchior, Laura E. Condon, Reed M. Maxwell

مصطلحات موضوعية: Hydrology, Natural Resource Management, Water Quality Engineering, Water Resources Engineering, Environmental Politics, machine learning, physics-based hydrological model, ParFlow-CLM, 2D soil moisture field, convolutional neural networks, meteorological forcing scenarios

العلاقة: https://figshare.com/articles/dataset/Data_Sheet_1_Training_machine_learning_with_physics-based_simulations_to_predict_2D_soil_moisture_fields_in_a_changing_climate_pdf/21309078Test

الإتاحة: https://doi.org/10.3389/frwa.2022.927113.s001Test
https://figshare.com/articles/dataset/Data_Sheet_1_Training_machine_learning_with_physics-based_simulations_to_predict_2D_soil_moisture_fields_in_a_changing_climate_pdf/21309078Test

مصطلحات الفهرس: fully integrated hydrological models, groundwater recharge, parflow-CLM, river-aquifer interactions, surface-subsurface flow, water table fluctuations, Article, Text

URL: https://www.repo.uni-hannover.de/handle/123456789/14957Test
https://doi.org/10.1029/2022wr032430Test
Water Resources Research 59 (2023), Nr. 3
1944-7973
0043-1397
https://doi.org/10.1029/2022wr032430Test